Business Data Analytics (BDA)

BDA 337   Introduction to Business Data Analytics   3 Units

This course will examine how data analysis technologies can be used to improve decision-making through the study of fundamental principles and techniques of data mining using real-world examples, cases, and software to place data-mining techniques in context, to develop data-analytic thinking, and to illustrate that proper application is as much an art as it is a science. Topics will include introduction to data mining, machine learning, and artificial intelligence: concepts and definitions, the data mining process, predictive and descriptive tasks.

BDA 338   Big Data Analytical Tools   3 Units

This course will introduce methods, tools, and applications used to extract and analyze big data with a focus on the use of these approaches and instruction on basic programming, design, and critical thinking skills necessary to use the applications. Prerequisites: BUS 201 and BUS 224.

BDA 436   Data Visualization   3 Units

Learn how to transform information from a format efficient for computation into a format efficient for human perception, cognition, and communication. Explore elements of computer graphics, human-computer interaction, perceptual psychology, and design in addition to data processing and computation. Learn to present data to an observer in a way that yeilds insight and understanding. The first part focuses on the infrastructure for data visualization. It introduces elementary graphics programming, focusing primarily on two-dimensional vector graphics and the programming platform for graphics. This infrastructure will also include lessons on the human side of visualization, studying human perception and cognition to gain a better understanding of the target of the data visualization. The second part will utilize the knowledge of graphics programming and human perception in the design and construction of visualizations, starting with simple charts and graphics and incorporating animation and user interactivity. The third part expands the data vizualization vocabulary with more sophisticated methods, including hierarchical layouts and networks. The final part focuses on visualization of database and data mining processes, with methods specifically focused on visualization of unstructured information, such as text, and systems for visual analytics that provide decision support. Prerequisite: BDA 337.

BDA 437   Optimization and Decision Analytics   3 Units

This course will introduce quantitative decision making tools. Quantitative decision making adds value to data by using it to build models that can help in the decision making process. Topics covered include property and density estimation, streaming and sampling selection, decision trees, recursive partitioning and Monte Carlo simulation. The focus will be on understanding the intuition behind the solution techniques used in analyzing big data and machine learning, as well as the application of these tools using analytic software packages. Prerequisite: BDA 337 and MTH 265.

BDA 475   Business Data Analytics Thesis   3 Units

This is a research based course culminating with a presentation of the student's thesis work. The work is aimed to address a real-world issue using new and traditional analytic techniques. Business Exam Fee required. Prerequisite: Business Major with Senior Standing and FIN 331, MGT 321, MKT 341.

BDA 490A   Internship: Business Data Analytics Major   1-2 Units

This course is a practical working experience in business data analytics where students meet with their internship director before beginning their internship for advice and approval on placement. Regular student reports and written feedback from the sponsoring business are required and must demonstrate the skills acquired during the internship. Prerequisites: Business Major with Junior or Senior standing and MGT 321 and BUS 224. Students must take a minimum cumulative total of two (2) units earned in one (1) unit credit hours. Offered as a Pass/No Pass course.

BDA 490B   Internship: Business Data Analytics Elective   1-6 Units

This course is a practical working experience in business data analytics where students meet with their internship director before beginning their internship for advice and approval on placement. Regular student reports and written feedback from the sponsoring business are required and must demonstrate the skills acquired during the internship. Prerequisites: Business Major with Junior or Senior standing and MGT 321 and BUS 224. Students may take a maximum cumulative total of six (6) units earned in one (1) unit credit hours. Offered as a Pass/No Pass course.